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Table 1.

Sequences and product numbers for target specific siRNA primers.

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Table 1 Expand

Fig 1.

Protocol for primary T cell culture displays phenotypic markers and transcriptional changes indicative of activation.

(A) ELISA results for secretion of 12 cytokines in resting and activated CD4 T cell cultures. Error bars represent mean ± S.E.M. (n = 3). (B) Histogram depicts expression of the T cell marker CD4 and various activation markers (CD25, CD69, CD71, CD62L, and CD40L) from FACS analysis of resting (red) and activated (blue) CD4 T cell cultures. (C) Breakdown of differential splicing events between resting and activated CD4 T cell culture based on RNASeq data using Alt-Analyze (ASPIRE > 0.2 & p-value < 0.1, S1 Table). (D) RT-qPCR validation of alternative splicing in RNAseq data for IL12RB2, LY96P, & KIF23. ASE–Alternatively Spliced Exon. Error bars represent mean ± S.D. (n = 3). (E) Breakdown of isoform changes by type between resting and activated T cells identified by Alt-Analyze in RNAseq data. (F) Three classes of gene expression are demonstrated after T cell activation: 1) DE, alone (5303); 2) DE+AS (1079); 3) AS, alone (1281). This data is also shown for DE—upregulated and DE—downregulated. DE–Differentially Expressed; AS–Alternatively Spliced.

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Fig 2.

RIPseq identifies critical immune genes bound to and spliced by U2AF2 upon activation.

(A) Hexbin plots comparing log2 (fpkm) values for U2AF2 RIPseq and RNAseq in resting (left) and activated (middle) CD4 T cell cultures. Right: Plot comparing the distribution of log2 (fold change) in RNAseq (red) and U2AF2 RIPseq (blue). (B) Heatmap of 1,927 significantly differentially bound genes in U2AF2 RIPseq (edgeR adjusted p-val < 0.05, n = 6/group). 957 increased and 970 decreased their binding to U2AF2 upon activation. (C) RT-qPCR of select differentially bound genes in U2AF2 RIPseq. Error bars represent mean ± S.D. (n = 3). (D) Cytoscape map of overlap of differentially expressed (upon activation) and differentially bound (to U2AF2) genes within significantly enriched ImmuneMap pathways. (E) Overlap of significantly differentially bound transcripts in U2AF2 RIPseq with differentially expressed & alternatively spliced genes in the RNAseq data. (F) Immune pathways significantly enriched (hypergeometric test adjusted p-value <0.05) for overlapping genes differentially bound during U2AF2 RIPseq and alternatively spliced (upon activation) in RNAseq data.

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Fig 3.

RIP-MS analysis reveals the activation-induced U2AF2-bound Core Interactome Members (CIMs) and Peripheral Interactome Members (PIMs).

(A) Venn diagram of the complete U2AF2 interactome established by RIP-MS in resting (204 total proteins) and activated CD4 T cells (229 total proteins) with the majority shared between the two states (n = 6). (B) Mean peptide ratios for proteins detected by SILAC as significantly changed upon activation after U2AF2 IP and MS (n = 3). Almost all proteins shared between resting and activated states, increase with activation. (C) SILAC ratios (activated/resting) and Western validation of pulldowns after IP for U2AF2 in resting and activated samples with and without RNAse A treatment (representative experiment). (D) Distribution of U2AF2 interacting proteins by “RNA binding”-related GO Catergories as a percentage of the total and -log of enrichment p-value (hypergeometric test adjusted p-value <0.05). (E) Venn diagram showing the Core Interactome Members (CIMs) as defined by RNAse A treatment of U2AF2 IPs followed by proteomic mass spectrometry (n = 4/group).

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Fig 3 Expand

Fig 4.

Knockdowns of U2AF2 CIMs and PIMs perturbs activation marker expression, cell proliferation and cytokine secretion.

(A) RT-qPCR validation of siRNA knockdown for U2AF1, SYNCRIP, ILF2, and SRRM2. Error bars represent mean ± S.D. (n = 6). Immunoblot analysis shows reduced protein levels for U2AF1 with protein expression quantified and normalized to tubulin (representative experiment). (B) Histogram depicts expression of the cell activation markers CD25 and CD62L from FACS analysis of resting and activated T cells treated with negative control siRNA (blue) or U2AF1 siRNA (green). (C) Proliferation of resting and activated CD4 T cells after siRNA treatment as measured by MTT assays. Error bars represent mean ± S.D. (n = 4). (D) ELISA results for secretion of 11 cytokines after knockdown of U2AF2 interactome members plotted as log2 fold changes. Error bars represent mean ± S.E.M. (n = 3). Statistical significance determined by Student’s t-test (*: p <0.05).

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Fig 4 Expand

Fig 5.

Knockdown of U2AF2 interactome members have specific impacts on the transcriptional landscape.

(A) Schematic for knockdown of U2AF2 interactome members and whole exome splicing microarray analysis in activated CD4 T cell cultures. (B) Volcano plots of significantly differentially expressed genes (up in siRNA–red; down in siRNA–green) after U2AF1, SRRM2, ILF2, or SYNCRIP knockdowns. Statistical significance determined by edgeR analysis (FDR adjusted p-value <0.05, n = 3). (C) RT-qPCR validation of select differentially expressed genes in U2AF1 (green) or SYNCRIP (orange) knockdowns. Error bars represent mean ± S.D. (n = 3). (D) Total genes differentially expressed and alternatively spliced in knockdowns. Alternatively spliced genes determined by Alt-Analyze (ASPIRE > 0.2); differentially expressed genes same as (B). (E) Cytoscape map of differentially expressed genes within significantly enriched immune related pathways (hypergeometric test adjusted p-value <0.05) affected by knockdown of U2AF1 (blue). Genes from these pathways differentially expressed in ILF2 (yellow), SYNCRIP (red), or all (green) knockdowns are highlighted.

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Fig 5 Expand

Fig 6.

U2AF1 knockdown in activated T cells causes significant splicing changes.

(A) Breakdown of differential splicing events affected by knockdown of U2AF1 in whole exon splicing microarray data using Alt-Analyze. (B) Top: RNAseq coverage plot of regions differentially spliced between resting and activated T cells for IL18R1, CASP2, ABI1. Middle: Normalized microarray intensities for junction probes (Exclusion/Inclusion) and exon probes (Cassette and Constitutive) from Control and U2AF1 siRNA samples are used by the Transcript Analysis Console (Affymetrix) to calculate the Splicing Index (SI). Greater probeset level intensity values in the Control siRNA samples correspond to negative SI values and positive SI represents increased intensity in the U2AF1 siRNA samples. Bottom: RT-qPCR Validation of alternative splicing after U2AF1 (green) or SYNCRIP (orange) knockdowns. ASE–Alternatively Spliced Exon. Error bars represent mean ± S.D. (n = 3).

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Fig 6 Expand

Fig 7.

U2AF1 knockdown impairs protein/RNA interactions with U2AF2 in activated T cells.

(A) Immunoblot analysis for binding of select U2AF2 interactome members after immunoprecipitation with U2AF2 antibody in activated cells with negative controls vs. U2AF1 siRNA. Protein expression quantified using the Li-Cor Odyssey and normalized to tubulin. (B) Totals of genes differentially bound to U2AF2 after knockdown of U2AF1 and SYNCRIP as compared to negative control siRNAs. Statistical significance determined by edgeR analysis (FDR adjusted p-value <0.05, n = 3). (C) RT-qPCR validation of selected differentially expressed genes after U2AF1 knockdown as revealed by U2AF2 RIP. Error bars represent mean ± S.D. (n = 3). (D) Cytoscape map of genes differentially bound to U2AF2 within KEGG pathways, Gene Ontology, and ImmuneMap after knockdown of U2AF1 (blue) or SYNCRIP (red). Statistical significance determined by hypergeometric test (multiple testing corrected p-value <0.05).

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Fig 8.

CD4 T cell activation and regulation of splicing by assembly of RNA binding protein complexes.

(A) T cell activation by antigen presentation and costimulation followed by induction of T cell specific intracellular signaling pathways. (B) Activation and translocation of transcription factors to the nucleus is followed by modular assembly of transcription factor complexes and initiation of transcription. (C) Assembly of U2AF centered RNA-protein-protein complexes mediates post-transcriptional regulation, including canonical and alternative splicing, of specific transcripts resulting in an appropriate activation-induced T cell response. Red box: A view of an individual pre-mRNA transcript, in Resting and Activated T cells, adds CIMs and PIMs to the current model for recruitment of the U2AF heterodimer to the 3’SS via splicing enhancers and suppressors that determine and regulate U2AF2 mediated canonical and alternative splicing. BP–branch point; ESE–exonic splicing enhancer; ESS–exonic splicing suppressor; ISE–intronic splicing enhancer; ISS–intronic splicing suppressor.

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